A New Parallel Asynchronous Cellular Genetic Algorithm for de Novo Genomic Sequencing

F. Pinel, B. Dorronsoro, P. Bouvry
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引用次数: 6

Abstract

This work proposes a new parallel asynchronous cellular genetic algorithm model for multi-core processors. The algorithm has been used for solving the DNA fragment assembly problem with the aim of finding highly accurate solutions in short computation times. This NP-Complete problem lies in reconstructing a DNA chain from multiple fragments that have previously been sequenced in a laboratory. The considered problem is a critical step in any genomic project, since the resulting chains are the basis for the entire work. Therefore, the quality of these chains is a major aspect for the correct development of the project. The proposed algorithm is able to find highly accurate results much faster than the other algorithms in the literature. Additionally, since it is parallel, it could be scalable to much larger problem instances, for which the methods typically used usually encounter difficulties. Finally, several new local search methods have been designed, and their influence on the performance of the algorithm has been analyzed.
一种新的并行异步细胞遗传算法用于从头基因组测序
本文提出了一种新的多核处理器并行异步细胞遗传算法模型。该算法已被用于解决DNA片段组装问题,目的是在较短的计算时间内找到高精度的解。这种np完全问题在于从先前在实验室中测序的多个片段重建DNA链。考虑到的问题是任何基因组计划的关键一步,因为得到的链是整个工作的基础。因此,这些链条的质量是项目正确发展的一个重要方面。与已有的算法相比,该算法能够更快地找到高精度的结果。此外,由于它是并行的,因此可以扩展到更大的问题实例,而通常使用的方法通常会遇到困难。最后,设计了几种新的局部搜索方法,并分析了它们对算法性能的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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